Analysis of EEG Features to Control Multiple Devices
Brain-Computer Interface (BCI) or Human-Machine Interface (HMI) now becoming vital engineering and technology field which applying EEG technologies to provide Assistive Technology (AT) to humans. This paper presents the analysis of EEG signals from various human cognitive or mental states to determi...
| Main Authors: | , , , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
Universiti Malaysia Pahang
2018
|
| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/22385/ http://umpir.ump.edu.my/id/eprint/22385/1/25.%20Analysis%20of%20EEG%20Features%20to%20Control%20Multiple%20Devices.pdf |
| _version_ | 1848821583060140032 |
|---|---|
| author | Rashid, Mamunur Norizam, Sulaiman Mahfuzah, Mustafa M. S., Jadin M. S., Najib |
| author_facet | Rashid, Mamunur Norizam, Sulaiman Mahfuzah, Mustafa M. S., Jadin M. S., Najib |
| author_sort | Rashid, Mamunur |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Brain-Computer Interface (BCI) or Human-Machine Interface (HMI) now becoming vital engineering and technology field which applying EEG technologies to provide Assistive Technology (AT) to humans. This paper presents the analysis of EEG signals from various human cognitive or mental states to determine the suitable EEG features that can be employed to control multiple devices. Here, EEG features in term of average of power spectrum, standard deviation of power spectrum and spectral centroid of power spectrum are selected to recognize human mental or cognitive state from 3 difference exercises; i) solving math problem, ii) Playing game and iii) do nothing (relax). We have calculated average power spectrum, average standard deviation of power spectrum and average spectral centroid of power spectrum of alpha and beta band for three mental exercises. |
| first_indexed | 2025-11-15T02:27:39Z |
| format | Conference or Workshop Item |
| id | ump-22385 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T02:27:39Z |
| publishDate | 2018 |
| publisher | Universiti Malaysia Pahang |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-223852019-10-09T03:10:48Z http://umpir.ump.edu.my/id/eprint/22385/ Analysis of EEG Features to Control Multiple Devices Rashid, Mamunur Norizam, Sulaiman Mahfuzah, Mustafa M. S., Jadin M. S., Najib TK Electrical engineering. Electronics Nuclear engineering Brain-Computer Interface (BCI) or Human-Machine Interface (HMI) now becoming vital engineering and technology field which applying EEG technologies to provide Assistive Technology (AT) to humans. This paper presents the analysis of EEG signals from various human cognitive or mental states to determine the suitable EEG features that can be employed to control multiple devices. Here, EEG features in term of average of power spectrum, standard deviation of power spectrum and spectral centroid of power spectrum are selected to recognize human mental or cognitive state from 3 difference exercises; i) solving math problem, ii) Playing game and iii) do nothing (relax). We have calculated average power spectrum, average standard deviation of power spectrum and average spectral centroid of power spectrum of alpha and beta band for three mental exercises. Universiti Malaysia Pahang 2018-07 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/22385/1/25.%20Analysis%20of%20EEG%20Features%20to%20Control%20Multiple%20Devices.pdf Rashid, Mamunur and Norizam, Sulaiman and Mahfuzah, Mustafa and M. S., Jadin and M. S., Najib (2018) Analysis of EEG Features to Control Multiple Devices. In: National Conference for Postgraduate Research (NCON-PGR 2018) , 28-29 August 2018 , Universiti Malaysia Pahang, Gambang, Pahang. pp. 1-7.. (Unpublished) (Unpublished) |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Rashid, Mamunur Norizam, Sulaiman Mahfuzah, Mustafa M. S., Jadin M. S., Najib Analysis of EEG Features to Control Multiple Devices |
| title | Analysis of EEG Features to Control Multiple Devices |
| title_full | Analysis of EEG Features to Control Multiple Devices |
| title_fullStr | Analysis of EEG Features to Control Multiple Devices |
| title_full_unstemmed | Analysis of EEG Features to Control Multiple Devices |
| title_short | Analysis of EEG Features to Control Multiple Devices |
| title_sort | analysis of eeg features to control multiple devices |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/22385/ http://umpir.ump.edu.my/id/eprint/22385/1/25.%20Analysis%20of%20EEG%20Features%20to%20Control%20Multiple%20Devices.pdf |